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Published for SISSA by SpringerReceived: June 27, 2015 Revised: September 20, 2015 Accepted: October 12, 2015 Published: November 11, 2015
Search for neutral MSSM Higgs bosons decaying into
a pair of bottom quarks
The CMS collaboration
E-mail: cms-publication-committee-chair@cern.ch
Abstract: A search for neutral Higgs bosons decaying into a b¯b quark pair and produced
in association with at least one additional b quark is presented. This signature is sensitive to the Higgs sector of the minimal supersymmetric standard model (MSSM) with large values of the parameter tan β. The analysis is based on data from proton-proton collisions at a center-of-mass energy of 8 TeV collected with the CMS detector at the LHC, corresponding
to an integrated luminosity of 19.7 fb−1. The results are combined with a previous analysis
based on 7 TeV data. No signal is observed. Stringent upper limits on the cross section times branching fraction are derived for Higgs bosons with masses up to 900 GeV, and
the results are interpreted within different MSSM benchmark scenarios, mmax
h , m mod+
h ,
mmod−h , light-stau and light-stop. Observed 95% confidence level upper limits on tan β,
ranging from 14 to 50, are obtained in the mmod+h benchmark scenario.
Keywords: Supersymmetry, Hadron-Hadron Scattering, Beyond Standard Model, Higgs physics
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Contents1 Introduction 1
2 The CMS detector 3
3 Event reconstruction and simulation 3
4 Trigger and event selection 4
5 Background model 6 6 Signal modeling 8 6.1 Signal templates 8 6.2 Signal efficiency 9 6.3 Fitting procedure 9 7 Systematic uncertainties 10 8 Results 11 8.1 Background-only fit 11
8.2 Combined fit of signal and background templates 11
8.3 Upper limits on cross sections times branching fractions 12
8.4 Interpretation within the MSSM 13
9 Summary 15
A Signal efficiency 17
B Exclusion limits 18
The CMS collaboration 25
1 Introduction
The discovery of a Higgs boson with a mass around 125 GeV [1–3] marked a milestone for
elementary particle physics. While the measured properties of the observed boson are in agreement with the expectations of the standard model (SM) with the current experimental precision, this particle could well be the first visible member of an extended Higgs sector, which would be a direct indication of new physics. Extended Higgs sectors are possible
in various theoretical models, such as Supersymmetry [4–7], which relates fermionic and
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bosons as well as a superpartner to each SM particle. The superpartners provide potential
dark-matter candidates [8], and their contribution to quantum-loop corrections can lead
to a unification of the gauge couplings at higher energies [9]. Moreover, the problem of
the quadratic divergence of the Higgs boson mass at high energies [10] is solved naturally
through cancellation of loop terms by the superpartners.
The minimal supersymmetric extension of the SM (MSSM) [5] contains two scalar
Higgs doublets, which result in two charged Higgs bosons, H±, and three neutral ones,
jointly denoted as φ. Among the latter are two CP-even (h, H) and one CP-odd state (A). The recently discovered boson with a mass near 125 GeV might then be interpreted as one of the neutral CP-even states. Two parameters, generally chosen as the mass of
the pseudoscalar Higgs boson mA and the ratio of the vacuum expectation values of the
two Higgs doublets, tan β = v2/v1, define the properties of the Higgs sector in the MSSM
at tree level. For tan β values larger than one, the couplings of the Higgs field to down-type fermions are enhanced relative to those to the up-down-type fermions. Furthermore, the A boson is nearly degenerate in mass with either the h or H boson. These effects enhance the combined cross section for producing these Higgs bosons in association with b quarks
by a factor of ≈2 tan2β. The decay φ → bb is expected to have a high branching fraction
(≈90%), even at large values of the Higgs boson mass [11].
Measurements at the CERN LHC in the φ → τ τ decay mode [12–15] have lead to the
most stringent constraints on tan β so far, with exclusion limits in the range 4–60 in the
mass interval of 90–1000 GeV. Preceding limits had been obtained by the LEP [16] and
Tevatron experiments [17–19]. Also the φ → µµ decay mode has been investigated [13,20].
Besides extending the MSSM Higgs boson search to an independent channel, the φ → bb
decay mode is particularly sensitive to the higgsino mass parameter µ [21], and thus to
the bottom quark Yukawa coupling. In the φ → τ τ channel, the sensitivity to µ is much smaller due to a partial cancellation of the respective radiative corrections between the
contributions to the production and decay processes [21]. Beyond the MSSM interpretation,
lepton-specific two-Higgs-doublet models (2HDM) [22] may allow for enhanced couplings
of down-type quarks relative to leptons. The bb decay mode is also relevant in the more general context of exotic resonance searches, motivated for example by dark-matter models
involving mediator particles with a large coupling to b quarks [23,24].
Searches in the φ → bb decay mode have initially been performed at LEP [16] and by
the CDF and D0 experiments [25] at the Tevatron collider. The first and so far the only
analysis at the LHC in this channel has been performed by the CMS experiment, using the
7 TeV data, and set significantly more stringent bounds in the mass range 90–350 GeV [26].
In this article, the CMS search is extended by adding the data set comprising 19.7 fb−1
of proton-proton collision data, collected at a center-of-mass energy of 8 TeV, and by the use of a refined methodology. The higher integrated luminosity as well as the greater center-of-mass energy allow extension of the search up to a mass of 900 GeV.
The search is performed for neutral MSSM Higgs bosons φ with masses mφ≥ 100 GeV
that are produced in association with at least one b quark and decay to bb; an illustration of
the signal process is given by the diagrams in figure1. The signal is thus searched for in final
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φ g ¯b g b ¯b b φ g b b ¯b b φ g b b ¯b bFigure 1. Example Feynman diagrams of the signal processes.
jet is made, since its kinematic distributions extend significantly beyond the available acceptance, and the resulting signal efficiency would be very low. Events are selected by specialized triggers that identify b jets already at the online level. This is important to suppress the large rate of multijet production at the LHC. The analysis searches for a
peak in the invariant mass distribution of the two b jets with the highest pT values, which
are assumed to originate from the Higgs boson decay. The dominant background is the production of heavy-flavor multijet events containing either three b jets, or two b jets plus a third jet originating from either a charm quark, a light-flavor quark or a gluon, which is misidentified as a b quark jet. For the final limits, the results of the 8 TeV analysis are
combined with the previous 7 TeV analysis [26].
2 The CMS detector
The central feature of the CMS detector is a superconducting solenoid of 6 m internal di-ameter, providing a magnetic field of 3.8 T. Within the field volume, the inner tracker is formed by a silicon pixel and strip tracker. It measures charged particles within the pseu-dorapidity range |η| < 2.5. The tracker provides a transverse impact parameter resolution
of approximately 15 µm and a resolution on pT of about 1.5% for 100 GeV particles. Also
inside the field volume are a crystal electromagnetic calorimeter, and a brass and scintilla-tor hadron calorimeter. Muons are measured in gas-ionization detecscintilla-tors embedded in the steel flux-return yoke, in the pseudorapidity range |η| < 2.4, with detector planes made using three technologies: drift tubes, cathode strip chambers, and resistive-plate
cham-bers. Matching muons to tracks measured in the silicon tracker results in a pT resolution
between 1% and 5%, for pT values up to 1 TeV. Forward calorimetry extends the coverage
provided by the barrel and endcap detectors up to |η| < 5. A detailed description of the CMS detector, together with a definition of the coordinate system used and the relevant
kinematic variables, can be found in ref. [27].
3 Event reconstruction and simulation
A particle-flow algorithm [28, 29] is used to reconstruct and identify all particles in the
event, i.e. electrons, muons, photons, charged hadrons, and neutral hadrons, with an opti-mal combination of all CMS detectors systems.
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The reconstructed primary vertex with the largest p2
T-sum of its associated tracks is
chosen as the vertex of the hard interaction and used as reference for the other physics objects.
Jets are clustered from the reconstructed particle candidates using the anti-kT
algo-rithm [30] with a distance parameter of R = 0.5, and each jet is required to pass
dedi-cated quality criteria to suppress the impact of instrumental noise and misreconstruction. Contributions from additional proton-proton interactions within the same bunch crossing (pileup) affect the jet momentum measurement. To mitigate this effect, charged particles associated with other vertices than the reference primary vertex are discarded in the jet reconstruction, and residual contributions (e.g. from neutral particles) are accounted for
using a jet-area based correction [31]. Jets originating entirely from pileup interactions
are identified and rejected based on vertex and jet-shape information [32]. Jet energy
cor-rections are derived from simulation, and are confirmed with in situ measurements of the
energy balance in dijet and Z/γ+jet events [33].
For the offline identification of b jets, the combined secondary vertex (CSV)
algo-rithm [34] is used. This algorithm combines information on track impact parameters and
secondary vertices within a jet in a single likelihood discriminant that provides a good separation between b jets and jets of other flavors. Secondary-vertex reconstruction is
performed with an inclusive vertex search amongst the tracks associated with a jet [35].
Simulated samples of signal and background events, also referred to as Monte Carlo
(MC) samples, were produced using the pythia [36] and MadGraph [37] event generators
and include pileup events. The response of the CMS detector is modeled with Geant4 [38].
The MSSM Higgs signal samples, pp → bbφ+X with φ → bb, were produced at leading
order in the 4-flavor scheme with pythia version 6.4.12. The pT and η distributions of the
leading associated b jet are in good agreement with the next-to-leading order (NLO)
cal-culations [39]. The multijet background from quantum chromodynamics (QCD) processes
has been produced with pythia, while for tt +jets events the MadGraph event generator was used in its version 5.1.5.11. For all generators, fragmentation, hadronization, and the
underlying event have been modeled using pythia with tune Z2∗. The most recent pythia
6 Z2* tune is derived from the Z1 tune [40], which uses the CTEQ5L parton distribution
functions (PDF) set, whereas Z2* adopts the CTEQ6L [41] PDF set.
4 Trigger and event selection
A major challenge to this analysis is posed by the huge hadronic interaction rate at the LHC, and it is addressed with a dedicated trigger scheme, designed especially to suppress the QCD multijet background. Only events with at least two jets in the pseudorapidity range of |η| ≤ 1.74 are selected. The leading jet (here and in the following the jets are ordered by
decreasing pT) is required to have pT > 80 GeV, while the subleading jet must have pT >
70 GeV. Furthermore, the event is only accepted if the absolute value of the difference in
pseudorapidity between any two jets fulfilling the pTand η requirements is less than or equal
to 1.74. The tight online requirements on the angular variables of the jets are introduced to reduce the trigger rates while preserving the signal significances in the probed mass range of
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the Higgs bosons. At the trigger level, b jets are identified using an algorithm that requires at least two tracks with high 3D impact parameter significance to be associated with the jet. At least two jets within the event must meet the online b tagging criteria to be accepted
by the trigger. The efficiency of the jet-pT requirements in the trigger are derived from the
data with zero-bias triggered events. The online b tagging efficiencies relative to the offline b tagging selection are obtained from simulations of QCD events generated with pythia and scaled to account for the different b tagging efficiencies between data and simulation. The total trigger efficiency for events satisfying the offline selection requirements detailed below ranges from 46–62% over the Higgs boson mass range of 100–900 GeV.
The offline selection requires events to have the two leading jets within |η| ≤ 1.65 to be fully within the pseudorapidity windows of the trigger, and the third leading jet
within |η| ≤ 2.2. The three leading jets must also pass pT thresholds of 80, 70 and 20 GeV,
respectively. In addition, the two leading jets must have a pseudorapidity difference of
|∆η12| ≤ 1.4, because the QCD multijet background increases significantly with respect
to the expected signal with increasing |∆η12|. A minimal pairwise separation of ∆R > 1
between the three leading jets, where ∆R = √(∆η)2+ (∆φ)2 and ∆η and ∆φ are the
pseudorapidity and azimuthal angle differences (in radians) between the two jets, is imposed to suppress background from b quark pairs arising from gluon splitting.
In the following, “triple-b-tag” and “double-b-tag” samples are introduced, which play crucial roles in the analysis. The triple-b-tag sample is the basis for the signal search. It is defined by requiring all three leading jets to satisfy a tight CSV b tagging selection require-ment at a working point characterized by a misidentification probability for light-flavor jets
(attributed to u, d, s, or g partons) of about 0.1% at an average jet pTof 80 GeV. The
typi-cal corresponding efficiency for b jets is about 50–60% in the central pseudorapidity region. The total number of events passing the trigger and offline selections is approximately 69 k. The double-b-tag sample plays a key role in the estimation of the multijet background. In this selection, only two of the three leading jets must pass the tight CSV b tagging requirement. The total number of double-b-tag events remaining after the trigger and offline selections is about 2.4 M. While this definition does not explicitly exclude the triple-b-tag events, the potential signal contribution is negligible due to the size of the QCD multijet background in the double-b-tag sample, and a veto would lead to distortions in
the background model described in section 5.
An additional flavor-sensitive quantity, the secondary vertex mass sum of a jet, ΣMSV,j,
is introduced to further improve the separation between jets of different flavor on top of the CSV b tagging requirement. It is defined as the sum of the invariant masses calculated from the tracks forming secondary vertices inside a jet, and thus provides additional separation power. The extension of the signal mass range compared to the previous 7 TeV analysis
implies that the jets can have larger pT, with the consequence that b-tagged jets from
background events have a higher probability to contain two heavy flavor quarks instead of at most one. This can occur for example if a very energetic gluon splits into a pair of b or c quarks with a narrow opening angle. For this reason, b and c quark pairs merged into the same jet, labeled as “b2” and “c2”, respectively, are treated separately from the cases of unmerged b and c quarks, labeled “b1” and “c1”, respectively.
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ΣMSV,j [GeV] Bj 0–1 0 1–2 1 2–3 2 >3 3 B3 B1+ B2 0–1 2–3 4–6 0–1 0 1 2 2 3 4 5 3 6 7 8Table 1. Left: definition of the index Bj according to the value of the secondary vertex mass sum of the jet. Right: definition of the values of the combined event b tagging estimator X123 for all combinations of the secondary vertex mass sum indices B1, B2, and B3.
The subsequent analysis will use the secondary vertex mass information to categorize events and to build background templates. Therefore, the secondary vertex mass sums of
the three leading jets are combined into a condensed event b tagging estimator, X123. The
construction of this estimator is shown in table 1. Each selected jet j, where j is the rank
of the jet in order of decreasing pT, is assigned an index Bj, which can take one of the four
possible integer values from 0–3 according to its secondary vertex mass sum value, as shown
in table1(left). For jets with no reconstructed secondary vertex, Bj is also set to zero. The
definition of these index regions is motivated by the population of the secondary vertex mass
sum by the different jet flavors. From the three indices B1, B2, and B3, a combined event
b tagging variable X123 is constructed as shown in table1 (right). By definition, the event
b tagging variable X123 can assume nine possible values ranging from 0 to 8. The events
are then categorized according to the value of X123, with the rationale of having sufficient
statistics in each bin. The signal is searched for in the two-dimensional spectrum formed
by the invariant mass of the two leading jets, M12, and the event b tagging variable X123.
5 Background model
The main background for this analysis originates from QCD multijet production, with at least two energetic jets actually containing b hadrons, and a third jet that passes the b tagging selection but possibly as a result of a mistag. Since this type of background cannot be accurately predicted by MC simulation, it is estimated from the data using
control samples. The chosen method is similar to the one used in ref. [42]. The background
is modeled by a combination of templates, which are constructed from the double-b-tag sample. Only the shape of these background templates is relevant, since the normalization will be determined by the fit to the data.
Three categories of events are distinguished in the double-b-tag sample, which are denoted as xbb, bxb and bbx depending on whether the jet with the highest,
second-highest or third-second-highest pT is exempt from the b-tag requirement. In this notation the
three jets are referred to in order of decreasing pT.
From these three double-b-tag categories, background templates are constructed by weighting each untagged jet with the b tagging probability according to its assumed flavor. In the template nomenclature, the convention is to indicate the assumed flavor with a
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[GeV] 12 M 0 100 200 300 400 500 600 700 800 a.u. / GeV 0.0 0.2 0.4 0.6 0.8 1.0 (8 TeV) -1 CMS, 19.7 fb (B2+B1+C2,b)b (C1,b)b (Q,b)b bb(B2+B1+C2) bb(C1+Q) 123 X 0 1 2 3 4 5 6 7 8 a.u. 0.0 0.2 0.4 0.6 0.8 1.0 (8 TeV) -1 CMS, 19.7 fb (B2+B1+C2,b)b (C1,b)b (Q,b)b bb(B2+B1+C2) bb(C1+Q)Figure 2. Projections of M12(left) and X123(right) for the five background templates used in the fit. The vertical scale is shown in arbitrary units.
capital letter, and it can be one of the five options Q, C1, B1, C2, and B2, where Q refers to light quarks or gluons, while C1 and C2 refer to a jet with a single charm quark and a pair of charm quarks, respectively. Similarly, B1 and B2 refer to jets assumed to contain a single bottom quark and a pair of bottom quarks, respectively. The total number of templates is therefore 15. Each background template is a binned distribution in the
two-dimensional space spanned by M12, the dijet mass of the two leading jets, and the event
b tagging variable X123. For the construction of each template, each event is weighted
with the b tagging probability corresponding to the assumed flavor of the untagged jet. This weight accounts for the effect of the b tagging discriminant threshold. The b tagging probability for each flavor is determined with simulated QCD multijet events, where the flavor selection is based on Monte Carlo truth information. Data/MC scale factors for the
b tagging efficiencies are applied where appropriate [34]. Since the b tagging efficiency has
a characteristic dependence on pT and η for each flavor, the weighting results in different
shapes of the M12 distributions. The X123 dimension of the templates is modeled in the
following way: in a given M12bin, an event can contribute to different X123bins depending
on the flavor of its jets and its kinematics. For the two b-tagged jets, the secondary vertex mass sum information is taken as measured. For the untagged jet, each of the four possible values of the secondary vertex mass sum index is taken into account with a weight
according to the probability that a jet with given flavor, pT and η will assume this value.
These probabilities, parametrized as a function of the jet pT and η, were determined from
simulated events, and validated in control data samples.
Two additional corrections are applied to the templates. The first correction addresses a contamination in the double-b-tag sample from non-bb events at the level of a few per-cent. This contamination is estimated directly from the data using a negative b tagging
im-JHEP11(2015)071
pact parameter of the tracks, ordered from the most negative impact parameter significance upward. A second correction is required since the online b tagging patterns are different in the double- and the triple-b-tag samples. In double-b-tag events, the two online b tags usually coincide with the offline b tags, while in triple-b-tag events the online b tags can be assigned to any two-jet subset of the three leading jets. The correction is computed from simulated QCD multijet events, and is applied in the form of additional weights to the events in the double-b-tag sample.
Similarity in shape between some templates leads to unnecessary redundancy. For this
reason, similar templates are combined using a χ2-based metric to guide the decisions.
The relative weights in a combination are taken from MC. In the cases where one of the two leading jets is untagged, and the flavor assumption is the same, e.g. Qbb, and bQb, the templates are combined, resulting in a merged template (Q,b)b = Qbb + bQb. By analogy, also (C1,b)b, (B1,b)b, (C2,b)b, and (B2,b)b are obtained. The resulting set of ten templates still shows many similarities. For this reason, (B1,b)b, (B2,b)b, and (C2,b)b are combined into a single template; bbB1, bbB2, and bbC2 into a second; and bbC1 and bbQ into a third. The total number of templates to be fitted in combination to the data is thus reduced to five, namely (B2+B1+C2,b)b, (C1,b)b, (Q,b)b, bb(B2+B1+C2), and
bb(C1+Q). The projections of the M12 and X123 variables are shown in figure 2for these
five background templates.
Beyond QCD multijet production, top-quark pair (tt) events pose the largest potential background to the signal topology. The requirement of three b-tagged jets reduces this background substantially, since only two highly energetic b-tagged jets are expected from the decays of the top quarks. However, one of the W bosons can decay into a cs pair, and the c jet can be mistagged as b jet. Using the tt Monte Carlo sample, the tt contribution is found to be relatively small; the number of tt events passing the selections of the double-and triple-b-tag datasets it estimated to be about a factor of 70 smaller than the total amount of data in these samples. The invariant mass spectrum from tt is very similar to the one from the QCD multijet background, and does not show any narrow peaks. Since the tt events contribute to the double-b-tag sample, they are also taken into account in the background model.
6 Signal modeling
6.1 Signal templates
A signal template is obtained for each MSSM Higgs boson mass considered by applying the full selection to the corresponding simulated signal data set, for nominal masses in the range of 100–900 GeV. The sensitivity of this analysis does not extend down to cross sections as low as that of the SM Higgs boson. Thus, a signal model with a single mass peak
is sufficient, in contrast to the φ → τ τ analysis [14], where the signal model comprises the
three neutral Higgs bosons of the MSSM, one of which is SM-like. The projections for the
M12 and X123 distributions of the signal templates for three different Higgs boson masses
are shown in figure3. The shape of the mass distribution is dominated by the experimental
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[GeV] 12 M 0 100 200 300 400 500 600 700 800 a.u. / GeV 0.0 0.2 0.4 0.6 0.8 1.0 1.2 CMS Simulation (8 TeV) = 200 GeV φ m = 350 GeV φ m = 500 GeV φ m 123 X 0 1 2 3 4 5 6 7 8 a.u. 0.0 0.2 0.4 0.6 0.8 1.0 1.2 CMS Simulation (8 TeV) = 200 GeV φ m = 350 GeV φ m = 500 GeV φ mFigure 3. The M12 (left) and X123 (right) projections of the signal templates for Higgs boson masses of mφ = 200, 350 and 500 GeV. The vertical scale is shown in arbitrary units.
Higgs boson in the considered mass and tan β region is negligible in comparison with the detector resolution. At a mass of 500 GeV and tan β = 50, for example, the natural width of the mass peak is found to be 13 GeV, which is only ≈14% of the RMS of the reconstructed
mass distribution. The X123distributions show little variation with the MSSM Higgs boson
mass; they reflect the triple-b-quark signature.
6.2 Signal efficiency
The signal efficiency for each MSSM Higgs mass point is obtained from the simulated data sets. The efficiency of the kinematic trigger selection has been derived with data from control triggers and is applied by weighting. Scale factors to account for the different b
tagging efficiencies in data and MC [34] are also applied. The efficiency ranges between
0.17 and 6.38 per mille and peaks around 300 GeV. The detailed mass dependence is
shown in appendixA. The decrease of the efficiency for masses beyond 300 GeV is due to
the degradation of the b tagging efficiency at high jet pT. For masses around 300 GeV the
kinematic selections give rise to an efficiency of approximately 0.12, which is reduced to approximately 0.0065 when triple b tagging is required.
6.3 Fitting procedure
The overall two-dimensional distribution in the variables M12and X123is fitted by a model
combining the background templates and optionally a signal template. A binned likelihood technique is used. The relative contribution of each template is determined by the fit. The systematic uncertainties are represented by nuisance parameters that are varied in the fit according to their probability density functions.
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Source Type Target Impact
Online b tagging Rate Signal 11%
Integrated luminosity Rate Signal 0.1%
Jet trigger Rate + Shape Signal 0.1%
Jet energy scale Rate + Shape Signal 0.5%
Jet energy resolution Rate + Shape Signal 0.1%
Offline b tagging (bc) Rate + Shape Signal + Background 2–16%
Offline b tagging (udsg) Shape Background 0.2%
Template stat. uncertainty Shape Background 1–21%
Secondary vertex mass sum Shape Signal + Background 0.9%
bb purity correction Shape Background 3.4%
Online b tagging correction Shape Background 0.5%
Table 2. Systematic uncertainties and their relative impact on the expected limit. The values represent an average over the mass range from 100–900 GeV, except for the template statistical and the offline b tagging (bc) uncertainties, where ranges are given.
7 Systematic uncertainties
The following systematic uncertainties in the expected signal and background estimates affect the determination of the signal yield and/or its interpretation within the MSSM.
Uncertainties in the yields of the signal contributions include the uncertainty in the
luminosity estimate [43], the statistical uncertainties in the signal MC samples, and the
uncertainties of the relative online b tagging corrections. Also taken into account are the
QCD renormalization and factorization scale (µr, µf) uncertainties, the uncertainties due
to the parton distribution functions (PDF) and the strong coupling constant αs, and the
uncertainties in the underlying event and parton shower modeling, which all only affect the translation of the signal cross section into tan β in the MSSM interpretation. The impact of these uncertainties on the signal acceptance is not significant.
The rate as well as the shape of the signal contributions are also affected by the un-certainties in the trigger efficiencies, the jet energy scale, the jet energy resolution, and the pileup modeling, as well as the scale factors for the b-tag efficiency, the mistag rate, and the secondary vertex mass scale. The last three also affect the shapes of the background tem-plates (recall that only the shape is relevant for the background temtem-plates). The statistical uncertainty in the template shape, due to the limited size of the double-b-tag sample and due to the uncertainty in the offline b-tag efficiencies and mistag rates, are propagated into the templates and accounted for in the fitting procedure. Additional systematic uncertain-ties in the shapes of the background-templates arise from the impurity of the double-b-tag sample and the online b tag correction to the templates. The sources and types of
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1/GeV 12 dN/dM 0 100 200 300 400 500 600 Data (B2+B1+C2,b)b (C1,b)b (Q,b)b bb(B2+B1+C2) bb(C1+Q) Pre-fit bin-by-bin unc.= 30) β = 350 GeV, tan A (m φ bb × 10 (8 TeV) -1 CMS, 19.7 fb [GeV] 12 M 0 100 200 300 400 500 600 700 800 900 1000 Data/Bkg 0.95 1.00 1.05 Events 0 5000 10000 15000 20000 25000 Data (B2+B1+C2,b)b (C1,b)b (Q,b)b bb(B2+B1+C2) bb(C1+Q) Pre-fit bin-by-bin unc.
= 30) β = 350 GeV, tan A (m φ bb × 10 (8 TeV) -1 CMS, 19.7 fb 123 X 0 1 2 3 4 5 6 7 8 Data/Bkg 0.95 1.00 1.05
Figure 4. Projections of the dijet mass M12 (left) and event b-tag variable X123 (right) in the triple-b-tag sample, together with the corresponding projections of the fitted background templates. The hatched area shows the total bin-by-bin background uncertainty of the templates prior to the fit, which takes into account the limited size of the double-b-tag sample and the uncertainties of the offline b-tag efficiencies and mistag rates. For illustration, the signal contribution expected in the mmax
h benchmark scenario of the MSSM with mA= 350 GeV, tan β = 30, and µ = +200 GeV is overlayed, scaled by a factor 10 for better readability. In addition, the ratio of data to the background estimate is shown at the bottom.
8 Results
8.1 Background-only fit
In the first step, an unconstrained fit is performed without inclusion of a signal template, involving a linear combination of the background templates only. Results are shown in
fig-ure4and table3. The template-based background model describes the data well within the
uncertainty of the template fits with a goodness-of-fit of χ2/N
dof = 207.9/209, where Ndof
is the number of degrees of freedom, corresponding to a p-value of 0.51. As expected, the fit is dominated by templates involving triple b-jet signatures, whose fitted total contributions amount to ≈82%.
8.2 Combined fit of signal and background templates
In the second step, a signal template is included together with the background templates in the fit, with the relative fractions of signal and background templates allowed to vary freely. The fit is performed for all considered Higgs boson masses from 100 to 900 GeV. None of the fits shows any significant signal excess. Results for a Higgs boson mass of 350 GeV are
shown in figure 5 and table 3. At this mass point, the highest fluctuation in the fitted
Higgs boson production cross section is observed, corresponding to a local significance
of approximately 1.5 standard deviations. The goodness-of-fit is χ2/N
dof = 205.2/208,
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1/GeV 12 dN/dM 0 100 200 300 400 500 600 Data (350 GeV) φ bb (B2+B1+C2,b)b (C1,b)b (Q,b)b bb(B2+B1+C2) bb(C1+Q) Pre-fit bin-by-bin unc.(8 TeV) -1 CMS, 19.7 fb [GeV] 12 M 0 100 200 300 400 500 600 700 800 900 1000 Data/Bkg 0.95 1.00 1.05 Events 0 5000 10000 15000 20000 25000 Data (350 GeV) φ bb (B2+B1+C2,b)b (C1,b)b (Q,b)b bb(B2+B1+C2) bb(C1+Q) Pre-fit bin-by-bin unc.
(8 TeV) -1 CMS, 19.7 fb 123 X 0 1 2 3 4 5 6 7 8 Data/Bkg 0.95 1.00 1.05
Figure 5. Results from the combined fit of signal and background templates in the triple-b-tag sample, at the 350 GeV mass point. The left plot shows the projections of the dijet mass M12, the right plot the projections of the event b-tag variable X123. The red graph represents the fitted Higgs signal contribution. The hatched area shows the total bin-by-bin background uncertainty of the templates prior to the fit, which takes into account the limited size of the double-b-tag sample and the uncertainties of the offline b-tag efficiencies and mistag rates. In addition, the ratio of data to the background estimate is shown at the bottom.
Template Background-only fit Signal+background fit
fraction [%] fraction [%] (B2+B1+C2,b)b 51.3 ± 3.5 49.5 ± 3.9 (C1,b)b 1.3 ± 2.3 1.7 ± 3.1 (Q,b)b 1.2 ± 2.0 1.1 ± 1.5 bb(B2+B1+C2) 31.2 ± 3.2 32.2 ± 3.4 bb (C1+Q) 15.1 ± 0.9 15.0 ± 0.9 bbφ(m = 350 GeV) — 0.5 ± 0.3
Table 3. Relative contributions of the individual templates as determined by the background-only and by the signal+background fit for a Higgs boson mass hypothesis of 350 GeV.
8.3 Upper limits on cross sections times branching fractions
Cross sections are obtained from the fractions determined by the fit multiplied by the total number of data events after the selection in the signal region, and divided by the
corresponding signal efficiencies (section 6.2) and the integrated luminosity of 19.7 fb−1.
In the absence of any significant signal, the results are translated into upper limits on the cross section times the branching fraction, σ(pp → bφ + X) B(φ → bb), of a generic Higgs-like state in the mass range 100–900 GeV. For calculations of exclusion limits, the
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[GeV] φ m 100 200 300 400 500 600 700 800 900 ) [pb] b b → φ( B × +X) φ b → (pp σ 1 10 2 10 3 10 (8 TeV) -1 CMS, 19.7 fb 95% CL limit Expected expected σ 1 ± expected σ 2 ± ObservedFigure 6. Expected and observed upper limits at 95% CL on σ(pp → bφ + X) B(φ → bb) as a function of mφ, where φ denotes a generic neutral Higgs-like state.
The chosen test statistic, used to determine how signal- and background-like the data are, is based on the profile likelihood ratio. Systematic uncertainties are incorporated in the analysis via nuisance parameters and treated as pseudo-observables, following the
frequentist paradigm. These uncertainties have been listed in section 7.
The observed and the median expected 95% confidence level (CL) limits as a function
of the Higgs boson mass are shown in figure 6and listed in table 5in appendix B. The 1σ
and 2σ bands of the test statistic, including systematic uncertainties, are also shown.
8.4 Interpretation within the MSSM
The cross section limits shown in figure 6 are further translated into exclusion limits on
the MSSM parameters tan β and mA. The cross sections obtained with the four-flavor
NLO QCD calculation [47,48] and the five-flavor NNLO QCD calculation as implemented
in bbh@nnlo [49] for b + h/H/A associated production have been combined using the
Santander matching scheme [50]. The branching fractions were computed with the
Feyn-Higgs [51–54] and HDECAY [55,56] programs as described in ref. [11].
The observed and expected 95% CL median upper limits on tan β versus mA, together
with the 1σ and 2σ bands, are shown in figure 7 (left). They have been computed within
the traditional MSSM mmax
h benchmark scenario [57] with the higgsino mass parameter
µ = +200 GeV. The observed upper limits range from tan β about 20 in the low-mAregion
to about 50 at mA= 500 GeV, and extend the existing measurement at 7 TeV [26] into the
hitherto unexplored mAregion beyond 350 GeV. The model interpretation is not extended
to higher masses above 500 GeV because the theoretical predictions are not reliable for tan β much higher than 60.
While the cross section limits obtained from the 2011 and 2012 data cannot be com-bined directly due to the different center-of-mass energies, such a combination is possible
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[GeV] A m 100 150 200 250 300 350 400 450 500 β tan 10 20 30 40 50 60 (8 TeV) -1 CMS, 19.7 fb 95% CL limit Expected expected σ 1 ± expected σ 2 ± Observed scenario h max m = +200 GeV µ 3 GeV ± 125 ≠ h,H m [GeV] A m 100 150 200 250 300 350 400 450 500 β tan 10 20 30 40 50 60 (7 TeV) -1 (8 TeV) + 4.9 fb -1 CMS, 19.7 fb 95% CL limit Expected expected σ 1 ± expected σ 2 ± Observed 7 Te V ex pect ed scenario h max m = +200 GeV µ 3 GeV ± 125 ≠ h,H mFigure 7. Expected and observed upper limits at 95% CL for the MSSM parameter tan β versus mAin the mmaxh benchmark scenario with µ = +200 GeV. The excluded parameter space (observed limit) is indicated by the shaded area. Regions where the mass of neither of the CP-even MSSM Higgs bosons h or H is compatible with the discovered Higgs boson of 125 GeV within a range of 3 GeV are marked by the hatched areas. The left plot shows the result obtained with the 8 TeV data only, the right plot shows the result obtained after a combination with the 7 TeV data. For comparison, the expected limit of the 7 TeV data analysis [26] is overlayed.
from both data periods are shown in figure 7 (right). While the sensitivity is significantly
enhanced compared to the 7 TeV analysis [26] already up to 350 GeV, the addition of the
7 TeV result visibly improves the sensitivity in the low-mass area below 200 GeV. The
observed limit for tan β ranges down to about 14 at the lowest mA value considered.
Association of one of the CP-even MSSM Higgs bosons h and H with the measured state at a mass of 125 GeV within a margin of ±3 GeV that reflects the theoretical
un-certainties [21] leads to an indirect constraint on tan β. The incompatible regions in the
parameter space are illustrated by the hatched areas in both plots in figure 7. In the mmax
h
scenario, the MSSM parameters beyond tree level have been tuned such that mh becomes
as large as possible. As a result, large mA and already moderate values of tan β lead to
mh values that are higher than the measured Higgs boson mass. This apparent exclusion
of large tan β values is, however, an artificial consequence of the assumptions in the mmax
h
scenario. Recently, several new MSSM benchmark scenarios have been proposed, which
are more naturally compatible with the observed Higgs boson at 125 GeV [21], and among
them the mmod+h , mmod–
h , light-stop, and light-stau scenarios are also used in the following
for the interpretation of the results of this analysis. The observed and expected 95% CL exclusion limits in these scenarios with µ = +200 GeV, obtained with the combined 7 and
8 TeV data, are shown in figure8. (The term “stop” refers to the supersymmetric partner
of the top quark throughout this paper. Results for the τ -phobic and low-mHscenarios are
not shown because the analysis has sensitivity in a limited mass region only.) The limits
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[GeV] A m 100 150 200 250 300 350 400 450 500 β tan 10 20 30 40 50 60 (7 TeV) -1 (8 TeV) + 4.9 fb -1 CMS, 19.7 fb 95% CL limit Expected expected σ 1 ± expected σ 2 ± Observed scenario h mod+ m = +200 GeV µ 3 GeV ± 125 ≠ h,H m [GeV] A m 100 150 200 250 300 350 400 450 500 β tan 10 20 30 40 50 60 (7 TeV) -1 (8 TeV) + 4.9 fb -1 CMS, 19.7 fb 95% CL limit Expected expected σ 1 ± expected σ 2 ± Observed scenario h mod-m = +200 GeV µ 3 GeV ± 125 ≠ h,H m [GeV] A m 100 150 200 250 300 350 400 450 500 β tan 10 20 30 40 50 60 (7 TeV) -1 (8 TeV) + 4.9 fb -1 CMS, 19.7 fb 95% CL limit Expected expected σ 1 ± expected σ 2 ± Observed scenario t ~ = +200 GeV µ 3 GeV ± 125 ≠ h,H m [GeV] A m 100 150 200 250 300 350 400 450 500 β tan 10 20 30 40 50 60 (7 TeV) -1 (8 TeV) + 4.9 fb -1 CMS, 19.7 fb 95% CL limit Expected expected σ 1 ± expected σ 2 ± Observed scenario τ ∼ = +200 GeV µ 3 GeV ± 125 ≠ h,H mFigure 8. Expected and observed upper limits at 95% CL for the MSSM parameter tan β versus mA in the mmod+h , m
mod–
h , light-stop, and light-stau benchmark scenarios with µ = +200 GeV [21].
The aforementioned sensitivity of the φ → bb channel to the higgsino mass parameter µ
is evident in figure9, where the limit in the mmod+
h scenario is compared for different values
of µ. The dependence is particularly pronounced at higher mA; for example, the observed
upper limit on tan β varies from 30 for µ = −500 GeV to beyond 60 for µ = +500 GeV for
mA= 500 GeV. The limits are also listed in table 12in appendix B.
9 Summary
A search for a Higgs boson decaying into a pair of b quarks and accompanied by at least one additional b quark has been performed in proton-proton collisions at a center-of-mass
energy of 8 TeV at the LHC, corresponding to an integrated luminosity of 19.7 fb−1. The
data were taken with dedicated triggers using all-hadronic jet signatures combined with online b tagging. A selection of events with three b-tagged jets has been performed in the offline analysis. A signal has been searched for in the two-dimensional spectrum formed by
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[GeV] A m 100 200 300 400 500 600 700 800 900 β tan 10 20 30 40 50 60 (7 TeV) -1 (8 TeV) + 4.9 fb -1 CMS, 19.7 fb 95% CL limit Expected Observed = +500 GeV µ = +200 GeV µ = - 200 GeV µ = - 500 GeV µ scenario h mod+ m [GeV] µ -500 -400 -300 -200 -100 0 100 200 300 400 500 β tan 10 20 30 40 50 60 (7 TeV) -1 (8 TeV) + 4.9 fb -1 CMS, 19.7 fb 95% CL limit mA = 200 GeV Expected mA = 350 GeV Observed mA = 500 GeV scenario h mod+ mFigure 9. Expected and observed upper limits at 95% CL for the MSSM parameter tan β versus mAfor four different values of the higgsino mass parameter µ (left) and versus µ for three different values of mA(right) in the mmod+h scenario.
No evidence for a signal is found. The observed distributions are well described by a background model constructed from events in which only two of the three leading jets are required to be b tagged. Upper limits on the Higgs boson cross section times branching fraction are obtained in the mass region from 100–900 GeV, thus extending the search to considerably higher masses than those accessed by the previous 7 TeV analysis. The upper limits range from about 250 pb at the lower end of the mass range, to about 1 pb at 900 GeV.
The results are interpreted within the MSSM in the benchmark scenarios mmax
h , m mod+
h ,
mmod–
h , light-stau and light-stop, and lead to upper limits for the model parameter tan β as
a function of the mass parameter mA. In combination with the 7 TeV data, the observed
limit for tan β ranges down to about 14 at the lowest mA value of 100 GeV in the mmod+h
scenario with a higgsino mass parameter of µ = +200 GeV. The limit depends significantly on µ, varying from tan β = 30 for µ = −500 GeV to beyond 60 for µ = +500 GeV at
mA= 500 GeV.
Acknowledgments
We congratulate our colleagues in the CERN accelerator departments for the excellent performance of the LHC and thank the technical and administrative staffs at CERN and at other CMS institutes for their contributions to the success of the CMS effort. In ad-dition, we gratefully acknowledge the computing centers and personnel of the Worldwide LHC Computing Grid for delivering so effectively the computing infrastructure essential to our analyses. Finally, we acknowledge the enduring support for the construction and operation of the LHC and the CMS detector provided by the following funding agencies: BMWFW and FWF (Austria); FNRS and FWO (Belgium); CNPq, CAPES, FAPERJ, and FAPESP (Brazil); MES (Bulgaria); CERN; CAS, MoST, and NSFC (China); COL-CIENCIAS (Colombia); MSES and CSF (Croatia); RPF (Cyprus); MoER, ERC IUT and
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mφ[GeV] Efficiency [per mille]
100 0.17 140 0.57 160 1.03 200 2.85 300 6.38 350 6.32 400 6.08 500 5.07 600 3.85 700 2.90 900 1.39
Table 4. The total signal efficiency in per mille as a function of the Higgs boson mass mφ, for a center-of-mass energy of 8 TeV.
ERDF (Estonia); Academy of Finland, MEC, and HIP (Finland); CEA and CNRS/IN2P3 (France); BMBF, DFG, and HGF (Germany); GSRT (Greece); OTKA and NIH (Hungary); DAE and DST (India); IPM (Iran); SFI (Ireland); INFN (Italy); MSIP and NRF (Repub-lic of Korea); LAS (Lithuania); MOE and UM (Malaysia); CINVESTAV, CONACYT, SEP, and UASLP-FAI (Mexico); MBIE (New Zealand); PAEC (Pakistan); MSHE and NSC (Poland); FCT (Portugal); JINR (Dubna); MON, RosAtom, RAS and RFBR (Rus-sia); MESTD (Serbia); SEIDI and CPAN (Spain); Swiss Funding Agencies (Switzerland); MST (Taipei); ThEPCenter, IPST, STAR and NSTDA (Thailand); TUBITAK and TAEK (Turkey); NASU and SFFR (Ukraine); STFC (United Kingdom); DOE and NSF (U.S.A.). Individuals have received support from the Marie-Curie program and the European Re-search Council and EPLANET (European Union); the Leventis Foundation; the A. P. Sloan Foundation; the Alexander von Humboldt Foundation; the Belgian Federal Science Policy
Office; the Fonds pour la Formation `a la Recherche dans l’Industrie et dans l’Agriculture
(FRIA-Belgium); the Agentschap voor Innovatie door Wetenschap en Technologie (IWT-Belgium); the Ministry of Education, Youth and Sports (MEYS) of the Czech Republic; the Council of Science and Industrial Research, India; the HOMING PLUS program of the Foundation for Polish Science, cofinanced from European Union, Regional Development Fund; the Compagnia di San Paolo (Torino); the Consorzio per la Fisica (Trieste); MIUR project 20108T4XTM (Italy); the Thalis and Aristeia programs cofinanced by EU-ESF and the Greek NSRF; the National Priorities Research Program by Qatar National Re-search Fund; and Rachadapisek Sompot Fund for Postdoctoral Fellowship, Chulalongkorn University (Thailand).
A Signal efficiency
The signal efficiencies are summarized in table 4 and shown in figure 10 as a function of
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[GeV]
φm
100 200 300 400 500 600 700 800 900Signal efficiency
-4 10 -3 10 -2 10(8 TeV)
-1CMS, 19.7fb
CMS Simulation (8 TeV)Figure 10. The signal efficiency as a function of the Higgs boson mass mφ, for a center-of-mass energy of 8 TeV.
Mass [GeV] −2σ −1σ Median +1σ +2σ Observed
100 160.7 221.0 330.4 518.8 811.2 251.9 140 49.4 68.0 101.6 161.2 254.7 158.8 160 25.9 35.6 52.5 81.6 126.1 68.7 200 13.7 19.0 28.2 44.1 68.6 17.8 300 3.0 4.1 6.1 9.4 14.5 10.5 350 1.9 2.7 3.9 6.1 9.3 7.1 400 1.3 1.8 2.7 4.2 6.4 2.4 500 0.8 1.2 1.7 2.7 4.2 1.5 600 0.6 0.9 1.3 2.0 3.2 0.7 700 0.5 0.7 1.1 1.8 2.8 1.3 900 0.4 0.6 1.0 1.6 2.7 0.8
Table 5. Expected and observed 95% CL upper limits on σ(pp → bφ + X) B(φ → bb) in pb as a function of mφ, where φ denotes a generic Higgs-like state, as obtained from the 8 TeV data.
B Exclusion limits
The model-independent 95% CL limits on σ(pp → bφ + X) B(φ → bb) are listed in table 5
for different Higgs boson masses mφ. The 95% CL limits of (tan β, mA) are listed in tables6
to11for different MSSM benchmark scenarios with µ = +200 GeV and for different values
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Mass [GeV] −2σ −1σ Median +1σ +2σ Observed
100 14.4 17.4 22.0 29.3 39.4 18.8 140 15.5 18.4 22.9 30.1 40.1 29.4 160 13.6 16.2 20.2 26.4 34.9 23.5 200 15.2 18.1 22.8 29.9 40.0 17.7 300 18.0 21.0 25.9 33.4 43.9 34.9 350 21.8 25.4 31.0 39.7 52.2 42.6 400 25.1 29.3 36.0 46.2 — 33.9 500 36.4 42.7 52.9 — — 49.4
Table 6. Expected and observed 95% CL upper limits on tan β as a function of mAin the mmaxh , µ = +200 GeV, benchmark scenario obtained from the 8 TeV data only.
Mass [GeV] −2σ −1σ Median +1σ +2σ Observed
100 13.1 15.6 19.4 24.6 31.2 13.9 140 13.8 16.1 19.5 24.2 29.8 22.3 160 12.3 14.5 17.6 22.0 27.2 17.8 200 13.2 15.5 18.8 23.3 28.5 14.5 300 17.3 20.1 24.4 30.5 38.5 33.5 350 21.1 24.5 29.6 36.9 46.4 36.5 400 25.1 29.3 36.0 46.2 — 33.9 500 36.4 42.7 52.9 — — 49.4
Table 7. Expected and observed 95% CL upper limits on tan β as a function of mAin the mmaxh , µ = +200 GeV, benchmark scenario obtained from a combination of the 7 and 8 TeV data.
Mass [GeV] −2σ −1σ Median +1σ +2σ Observed
100 13.4 16.0 19.8 25.1 31.9 14.2 140 13.8 16.2 19.6 24.3 30.1 22.4 160 12.6 14.8 18.0 22.4 27.7 18.2 200 13.5 15.8 19.2 23.8 29.1 14.8 300 17.6 20.5 24.8 31.1 39.2 34.1 350 21.4 24.8 30.0 37.5 47.1 37.1 400 25.5 29.8 36.5 46.9 — 34.4 500 36.8 43.2 53.5 — — 50.0
Table 8. Expected and observed 95% CL upper limits on tan β as a function of mAin the mmod+h , µ = +200 GeV, benchmark scenario obtained from a combination of the 7 and 8 TeV data.
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Mass [GeV] −2σ −1σ Median +1σ +2σ Observed
100 12.7 15.0 18.3 22.8 28.3 13.4 140 13.1 15.2 18.1 22.2 26.9 20.6 160 11.9 13.9 16.7 20.5 24.9 16.9 200 12.8 14.9 17.9 21.7 26.1 13.9 300 16.5 18.9 22.6 27.7 33.9 30.1 350 19.8 22.7 26.9 32.7 39.7 32.4 400 23.2 26.7 32.0 39.7 49.7 30.4 500 32.3 37.1 44.4 55.1 — 41.9
Table 9. Expected and observed 95% CL upper limits on tan β as a function of mA in the mmod–h , µ = +200 GeV, benchmark scenario obtained from a combination of the 7 and 8 TeV data.
Mass [GeV] −2σ −1σ Median +1σ +2σ Observed
100 14.4 17.4 22.2 29.1 38.6 15.4 140 15.0 17.8 22.0 28.2 36.2 25.7 160 13.5 16.1 20.0 25.6 32.9 20.2 200 14.4 17.2 21.4 27.4 34.8 15.9 300 17.8 21.6 27.6 36.7 48.9 41.4 350 21.0 25.7 33.1 44.8 — 44.1 400 25.7 31.8 42.4 — — 39.0 500 40.3 52.1 — — — —
Table 10. Expected and observed 95% CL upper limits on tan β as a function of mAin the light-stau, µ = +200 GeV, benchmark scenario obtained from a combination of the 7 and 8 TeV data.
Mass [GeV] −2σ −1σ Median +1σ +2σ Observed
100 15.3 18.9 24.7 34.1 49.2 16.5 140 15.9 19.1 24.3 32.6 44.9 29.1 160 14.4 17.4 22.1 29.6 40.2 22.4 200 15.5 18.8 24.2 32.3 43.8 17.3 300 19.7 24.5 32.7 47.6 — 56.8 350 23.6 29.9 41.4 — — — 400 29.7 39.0 58.6 — — 51.7 500 52.5 — — — — —
Table 11. Expected and observed 95% CL upper limits on tan β as a function of mAin the light-stop, µ = +200 GeV, benchmark scenario obtained from a combination of the 7 and 8 TeV data.
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Mass [GeV] µ = −500 GeV µ = −200 GeV µ = +200 GeV µ = +500 GeV
100 12.9 (16.6) 13.7 (18.1) 14.2 (19.8) 16.1 (22.7) 140 18.2 (16.4) 19.9 (17.8) 22.4 (19.6) 26.1 (22.5) 160 15.5 (15.4) 16.7 (16.6) 18.2 (18.0) 20.8 (20.6) 200 13.1 (16.2) 14.0 (17.5) 14.8 (19.2) 16.6 (21.9) 300 24.2 (19.0) 27.6 (21.3) 34.1 (24.8) 41.0 (27.8) 350 25.1 (21.3) 29.7 (25.1) 37.1 (30.0) 43.8 (33.2) 400 23.5 (24.6) 28.2 (29.5) 34.4 (36.5) 39.0 (42.2) 500 30.3 (31.8) 37.8 (39.6) 50.0 (53.5) — (—) 600 33.2 (41.0) 42.3 (52.8) 57.5 (—) — (—) 700 54.3 (51.3) — (—) — (—) — (—)
Table 12. Observed (expected) 95% CL upper limits on tan β as a function of mA in the mmod+h benchmark scenario for different values of the higgsino mass parameter µ obtained from a combi-nation of the 7 and 8 TeV data.
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JHEP11(2015)071
The CMS collaborationYerevan Physics Institute, Yerevan, Armenia V. Khachatryan, A.M. Sirunyan, A. Tumasyan
Institut f¨ur Hochenergiephysik der OeAW, Wien, Austria
W. Adam, E. Asilar, T. Bergauer, J. Brandstetter, E. Brondolin, M. Dragicevic, J. Er¨o,
M. Flechl, M. Friedl, R. Fr¨uhwirth1, V.M. Ghete, C. Hartl, N. H¨ormann, J. Hrubec,
M. Jeitler1, V. Kn¨unz, A. K¨onig, M. Krammer1, I. Kr¨atschmer, D. Liko, T. Matsushita,
I. Mikulec, D. Rabady2, B. Rahbaran, H. Rohringer, J. Schieck1, R. Sch¨ofbeck, J. Strauss,
W. Treberer-Treberspurg, W. Waltenberger, C.-E. Wulz1
National Centre for Particle and High Energy Physics, Minsk, Belarus V. Mossolov, N. Shumeiko, J. Suarez Gonzalez
Universiteit Antwerpen, Antwerpen, Belgium
S. Alderweireldt, T. Cornelis, E.A. De Wolf, X. Janssen, A. Knutsson, J. Lauwers, S. Luyckx, S. Ochesanu, R. Rougny, M. Van De Klundert, H. Van Haevermaet, P. Van Mechelen, N. Van Remortel, A. Van Spilbeeck
Vrije Universiteit Brussel, Brussel, Belgium
S. Abu Zeid, F. Blekman, J. D’Hondt, N. Daci, I. De Bruyn, K. Deroover, N. Heracleous, J. Keaveney, S. Lowette, L. Moreels, A. Olbrechts, Q. Python, D. Strom, S. Tavernier, W. Van Doninck, P. Van Mulders, G.P. Van Onsem, I. Van Parijs
Universit´e Libre de Bruxelles, Bruxelles, Belgium
P. Barria, C. Caillol, B. Clerbaux, G. De Lentdecker, H. Delannoy, D. Dobur, G. Fasanella, L. Favart, A.P.R. Gay, A. Grebenyuk, T. Lenzi, A. L´eonard, T. Maerschalk, A. Marinov, L. Perni`e, A. Randle-conde, T. Reis, T. Seva, C. Vander Velde, P. Vanlaer, R. Yonamine,
F. Zenoni, F. Zhang3
Ghent University, Ghent, Belgium
K. Beernaert, L. Benucci, A. Cimmino, S. Crucy, A. Fagot, G. Garcia, M. Gul, J. Mccartin, A.A. Ocampo Rios, D. Poyraz, D. Ryckbosch, S. Salva, M. Sigamani, N. Strobbe, M. Tytgat, W. Van Driessche, E. Yazgan, N. Zaganidis
Universit´e Catholique de Louvain, Louvain-la-Neuve, Belgium
S. Basegmez, C. Beluffi4, O. Bondu, S. Brochet, G. Bruno, R. Castello, A. Caudron,
L. Ceard, G.G. Da Silveira, C. Delaere, D. Favart, L. Forthomme, A. Giammanco5,
J. Hollar, A. Jafari, P. Jez, M. Komm, V. Lemaitre, A. Mertens, C. Nuttens, L. Perrini,
A. Pin, K. Piotrzkowski, A. Popov6, L. Quertenmont, M. Selvaggi, M. Vidal Marono
Universit´e de Mons, Mons, Belgium
N. Beliy, G.H. Hammad
Centro Brasileiro de Pesquisas Fisicas, Rio de Janeiro, Brazil
W.L. Ald´a J´unior, G.A. Alves, L. Brito, M. Correa Martins Junior, T. Dos Reis Martins,
JHEP11(2015)071
Universidade do Estado do Rio de Janeiro, Rio de Janeiro, Brazil
E. Belchior Batista Das Chagas, W. Carvalho, J. Chinellato7, A. Cust´odio, E.M. Da Costa,
D. De Jesus Damiao, C. De Oliveira Martins, S. Fonseca De Souza, L.M. Huertas Guativa, H. Malbouisson, D. Matos Figueiredo, L. Mundim, H. Nogima, W.L. Prado Da Silva,
A. Santoro, A. Sznajder, E.J. Tonelli Manganote7, A. Vilela Pereira
Universidade Estadual Paulistaa, Universidade Federal do ABCb, S˜ao Paulo,
Brazil
S. Ahujaa, C.A. Bernardesb, A. De Souza Santosb, S. Dograa, T.R. Fernandez Perez Tomeia,
E.M. Gregoresb, P.G. Mercadanteb, C.S. Moona,8, S.F. Novaesa, Sandra S. Padulaa,
D. Romero Abad, J.C. Ruiz Vargas
Institute for Nuclear Research and Nuclear Energy, Sofia, Bulgaria
A. Aleksandrov, V. Genchev†, R. Hadjiiska, P. Iaydjiev, S. Piperov, M. Rodozov,
S. Stoykova, G. Sultanov, M. Vutova University of Sofia, Sofia, Bulgaria
A. Dimitrov, I. Glushkov, L. Litov, B. Pavlov, P. Petkov Institute of High Energy Physics, Beijing, China
M. Ahmad, J.G. Bian, G.M. Chen, H.S. Chen, M. Chen, T. Cheng, R. Du, C.H. Jiang,
R. Plestina9, F. Romeo, S.M. Shaheen, J. Tao, C. Wang, Z. Wang, H. Zhang
State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing, China
C. Asawatangtrakuldee, Y. Ban, Q. Li, S. Liu, Y. Mao, S.J. Qian, D. Wang, Z. Xu, W. Zou Universidad de Los Andes, Bogota, Colombia
C. Avila, A. Cabrera, L.F. Chaparro Sierra, C. Florez, J.P. Gomez, B. Gomez Moreno, J.C. Sanabria
University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, Split, Croatia
N. Godinovic, D. Lelas, D. Polic, I. Puljak
University of Split, Faculty of Science, Split, Croatia Z. Antunovic, M. Kovac
Institute Rudjer Boskovic, Zagreb, Croatia V. Brigljevic, K. Kadija, J. Luetic, L. Sudic University of Cyprus, Nicosia, Cyprus
A. Attikis, G. Mavromanolakis, J. Mousa, C. Nicolaou, F. Ptochos, P.A. Razis, H. Rykaczewski
Charles University, Prague, Czech Republic
JHEP11(2015)071
Academy of Scientific Research and Technology of the Arab Republic of Egypt, Egyptian Network of High Energy Physics, Cairo, Egypt
R. Aly11, E. El-khateeb12, T. Elkafrawy12, A. Lotfy13, A. Mohamed14, A. Radi15,12,
E. Salama12,15, A. Sayed12,15
National Institute of Chemical Physics and Biophysics, Tallinn, Estonia B. Calpas, M. Kadastik, M. Murumaa, M. Raidal, A. Tiko, C. Veelken
Department of Physics, University of Helsinki, Helsinki, Finland P. Eerola, J. Pekkanen, M. Voutilainen
Helsinki Institute of Physics, Helsinki, Finland
J. H¨ark¨onen, V. Karim¨aki, R. Kinnunen, T. Lamp´en, K. Lassila-Perini, S. Lehti, T. Lind´en,
P. Luukka, T. M¨aenp¨a¨a, T. Peltola, E. Tuominen, J. Tuominiemi, E. Tuovinen, L.
Wend-land
Lappeenranta University of Technology, Lappeenranta, Finland J. Talvitie, T. Tuuva
DSM/IRFU, CEA/Saclay, Gif-sur-Yvette, France
M. Besancon, F. Couderc, M. Dejardin, D. Denegri, B. Fabbro, J.L. Faure, C. Favaro, F. Ferri, S. Ganjour, A. Givernaud, P. Gras, G. Hamel de Monchenault, P. Jarry, E. Locci, M. Machet, J. Malcles, J. Rander, A. Rosowsky, M. Titov, A. Zghiche
Laboratoire Leprince-Ringuet, Ecole Polytechnique, IN2P3-CNRS, Palaiseau, France
S. Baffioni, F. Beaudette, P. Busson, L. Cadamuro, E. Chapon, C. Charlot, T. Dahms, O. Davignon, N. Filipovic, A. Florent, R. Granier de Cassagnac, S. Lisniak, L. Mas-trolorenzo, P. Min´e, I.N. Naranjo, M. Nguyen, C. Ochando, G. Ortona, P. Paganini, S. Regnard, R. Salerno, J.B. Sauvan, Y. Sirois, T. Strebler, Y. Yilmaz, A. Zabi
Institut Pluridisciplinaire Hubert Curien, Universit´e de Strasbourg,
Univer-sit´e de Haute Alsace Mulhouse, CNRS/IN2P3, Strasbourg, France
J.-L. Agram16, J. Andrea, A. Aubin, D. Bloch, J.-M. Brom, M. Buttignol, E.C. Chabert,
N. Chanon, C. Collard, E. Conte16, X. Coubez, J.-C. Fontaine16, D. Gel´e, U. Goerlach,
C. Goetzmann, A.-C. Le Bihan, J.A. Merlin2, K. Skovpen, P. Van Hove
Centre de Calcul de l’Institut National de Physique Nucleaire et de Physique des Particules, CNRS/IN2P3, Villeurbanne, France
S. Gadrat
Universit´e de Lyon, Universit´e Claude Bernard Lyon 1, CNRS-IN2P3, Institut
de Physique Nucl´eaire de Lyon, Villeurbanne, France
S. Beauceron, C. Bernet, G. Boudoul, E. Bouvier, C.A. Carrillo Montoya, J. Chasserat, R. Chierici, D. Contardo, B. Courbon, P. Depasse, H. El Mamouni, J. Fan, J. Fay, S. Gas-con, M. Gouzevitch, B. Ille, I.B. Laktineh, M. Lethuillier, L. Mirabito, A.L. Pequegnot, S. Perries, J.D. Ruiz Alvarez, D. Sabes, L. Sgandurra, V. Sordini, M. Vander Donckt, P. Verdier, S. Viret, H. Xiao
JHEP11(2015)071
Georgian Technical University, Tbilisi, Georgia
T. Toriashvili17
Institute of High Energy Physics and Informatization, Tbilisi State University, Tbilisi, Georgia
Z. Tsamalaidze10
RWTH Aachen University, I. Physikalisches Institut, Aachen, Germany
C. Autermann, S. Beranek, M. Edelhoff, L. Feld, A. Heister, M.K. Kiesel, K. Klein, M. Lipinski, A. Ostapchuk, M. Preuten, F. Raupach, J. Sammet, S. Schael, J.F. Schulte,
T. Verlage, H. Weber, B. Wittmer, V. Zhukov6
RWTH Aachen University, III. Physikalisches Institut A, Aachen, Germany M. Ata, M. Brodski, E. Dietz-Laursonn, D. Duchardt, M. Endres, M. Erdmann, S. Erdweg,
T. Esch, R. Fischer, A. G¨uth, T. Hebbeker, C. Heidemann, K. Hoepfner, D. Klingebiel,
S. Knutzen, P. Kreuzer, M. Merschmeyer, A. Meyer, P. Millet, M. Olschewski, K. Padeken, P. Papacz, T. Pook, M. Radziej, H. Reithler, M. Rieger, F. Scheuch, L. Sonnenschein,
D. Teyssier, S. Th¨uer
RWTH Aachen University, III. Physikalisches Institut B, Aachen, Germany
V. Cherepanov, Y. Erdogan, G. Fl¨ugge, H. Geenen, M. Geisler, F. Hoehle, B. Kargoll,
T. Kress, Y. Kuessel, A. K¨unsken, J. Lingemann2, A. Nehrkorn, A. Nowack, I.M. Nugent,
C. Pistone, O. Pooth, A. Stahl
Deutsches Elektronen-Synchrotron, Hamburg, Germany
M. Aldaya Martin, I. Asin, N. Bartosik, O. Behnke, U. Behrens, A.J. Bell, K. Borras, A. Burgmeier, A. Cakir, L. Calligaris, A. Campbell, S. Choudhury, F. Costanza, C. Diez Pardos, G. Dolinska, S. Dooling, T. Dorland, G. Eckerlin, D. Eckstein, T. Eichhorn, G. Flucke, E. Gallo, J. Garay Garcia, A. Geiser, A. Gizhko, P. Gunnellini, J. Hauk,
M. Hempel18, H. Jung, A. Kalogeropoulos, O. Karacheban18, M. Kasemann, P. Katsas,
J. Kieseler, C. Kleinwort, I. Korol, W. Lange, J. Leonard, K. Lipka, A. Lobanov,
W. Lohmann18, R. Mankel, I. Marfin18, I.-A. Melzer-Pellmann, A.B. Meyer, G. Mittag,
J. Mnich, A. Mussgiller, S. Naumann-Emme, A. Nayak, E. Ntomari, H. Perrey, D. Pitzl,
R. Placakyte, A. Raspereza, P.M. Ribeiro Cipriano, B. Roland, M. ¨O. Sahin, P. Saxena,
T. Schoerner-Sadenius, M. Schr¨oder, C. Seitz, S. Spannagel, K.D. Trippkewitz, R. Walsh,
C. Wissing
University of Hamburg, Hamburg, Germany
V. Blobel, M. Centis Vignali, A.R. Draeger, J. Erfle, E. Garutti, K. Goebel, D. Gonzalez,
M. G¨orner, J. Haller, M. Hoffmann, R.S. H¨oing, A. Junkes, R. Klanner, R. Kogler,
T. Lapsien, T. Lenz, I. Marchesini, D. Marconi, D. Nowatschin, J. Ott, F. Pantaleo2,
T. Peiffer, A. Perieanu, N. Pietsch, J. Poehlsen, D. Rathjens, C. Sander, H. Schettler, P. Schleper, E. Schlieckau, A. Schmidt, J. Schwandt, M. Seidel, V. Sola, H. Stadie,
